Currently, more and more leaders of medium and large industrial companies are thinking about digital transformation of their enterprise. Each company is forced to strive to find a production optimization approach in order to remain competitive in the market. For industrial enterprises, this approach could be digital transformation using the ideas of Industry 4.0. Digital transformation of an enterprise is a complex and multifaceted process that affects almost all levels of production. This process is based on data both on the operation of individual pieces of equipment and on production as a whole, which must be collected, stored, aggregated, and transferred to various levels. Data collection can be carried out using various tools, as well as proven technologies,such as OPC (Open Platform Communications), and using modern solutions (for example, MT Connect technology, API control systems, etc.).
Ways to solve the problem
Every year there is an increasing number of systems for collecting data from technological equipment, such as, for example, MDC systems (MDC - Machine Data Collect). These systems, in fact, are a subclass of SCADA systems, but they solve a narrowly specialized task - collecting data for analytical research, or providing a limited set of necessary data to the operator of technological equipment. Often the object of application of MDC systems is numerical control equipment, while the following set of data is collected: the execution time of the control program, consumed resources (for example, electrical energy), errors that appear during operation, and much more.This data set allows you to analyze the operation of a machine or even an entire workshop to determine the reasons for downtime and the occurrence of irregular situations. But the prospects for the development of MDC systems seem to us broader. Among the range of possible tasks are the following: data collection from Programmable Logic Controllers, PAC systems and sensors using IoT technology; transferring data to powerful analytics platforms (e.g. Azure, AWS, Bosch IoT, etc.). Also, based on the results of work, it is possible to process and provide aggregated data in a format that is convenient for visual perception, which will further solve the problem of optimal implementation of the operator's interfaces of technological equipment.collection of data from Programmable Logic Controllers, PAC systems and sensors using IoT technology; transferring data to powerful analytics platforms (e.g. Azure, AWS, Bosch IoT, etc.). Also, based on the results of work, it is possible to process and provide aggregated data in a format that is convenient for visual perception, which will further solve the problem of optimal implementation of the operator's interfaces of technological equipment.collection of data from Programmable Logic Controllers, PAC systems and sensors using IoT technology; transferring data to powerful analytics platforms (e.g. Azure, AWS, Bosch IoT, etc.). Also, based on the results of the work, it is possible to process and provide aggregated data in a format that is convenient for visual perception, which will further solve the problem of optimal implementation of the operator's interfaces of technological equipment.which will further solve the problem of optimal implementation of the operator's interfaces for technological equipment.which will further solve the problem of optimal implementation of the operator's interfaces for technological equipment.
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